You get home from the supermarket only to find that you've forgotten a vital ingredient for your dinner. But there is good news that could make sure you never forget key ingredients again. Microsoft has teamed up with refrigerator company, Liebherr, to create a new'SmartDeviceBox' which reminds people which foods they need to stock up on. We've all been there - you get home from the supermarket only to find that you've forgotten a vital ingredient (stock image left). But Microsoft has teamed up with Liebherr, to create a new'SmartDeviceBox' (pictured right) which reminds people which foods they need The SmartDeviceBox is an internet-connected device that uses cameras and object recognition technology to track what is in a refrigerator.

The mobile marketing attribution analytics company AppsFlyer, and Chinese internet giant Tencent have announced a partnership to make AppsFlyer's analytics platform available for marketers to track the effectiveness of app install campaigns on Tencent Social Ads. "The app economy is quickly becoming a global economy, and this partnership with Tencent Social Ads, one of the biggest and most important distribution platforms in the world, opens up myriad possibilities for app marketers and developers looking to grow in China, while enabling us to expand our footprint in Asia and globally as well," said Elad Masiach, VP Partner Development at AppsFlyer. Google has added automatically generated insights of data into the Android and iOS versions of Google Analytics. This new feature is quite similar to the insights in plain English that are provided by products like BeyondCore, which was acquired by Salesforce very recently. Machine learning and artificial intelligence is used to convert raw data into credible information which "lets you see in 5 minutes what might have taken hours to discover previously", said Google in a company blog post. Salesforce announced the expansion of its Wave Analytics portfolio with new Salesforce Wave Apps for B2B Marketing and Financial Services, as well as 19 apps from ISV partners.

For four years, eBay has been collecting customer search data, along with search click-through rates and other customer interaction data, and feeding the information into its machine learning system. In an interview with InformationWeek, Dan Fain, the company's VP of engineering, outlined the steps being taken, and the business motiviation behind them. The use-cases are worth exploring for any IT professional looking to help improve a company's bottom line by applying machine learning to customer-facing applications. Search, customer click patterns, language translations, item recommendations, and image analysis are among the key ways machine learning is being put to use at eBay, according to Fain. The first, and most important, appliction of machine learning is to improve search functions on eBay.com, according to Fain. "We have several machine learning models working behind the scenes to ensure we get the best search results," said Fain in our interview.

In this special guest feature, Pallab Deb, Vice President and Global Head, Analytics at Wipro Limited, outlines how you can gain benefit from using your gut business instincts by combining them with extreme data insights. Pallab Deb in his current role heads the Wipro's Analytics service line which delivers state of the art analytics solutions to a global clientele. With his extensive experience in Information Technology, Pallab has not only held multiple leadership roles in Connected Enterprise Services (CES) service line of Wipro, client engagements & strategic alliances but also has led sales teams on complex consulting, system integration and outsourcing deals in North America and Europe in High Tech, Manufacturing, Retail & Consumer Goods, Life Sciences and Utilities industries delivering on aggressive sales growth targets for seven consecutive years. Organizations are tantalizingly close to a vast amount of data that can prove meaningful to business. There is a prodigious amount of text, visual and audio information flowing across media reports, company filings, government records, surveys, research documents, social media, messaging applications, blogs, email, IVR, machine logs, contracts, ERP, POS, CRM, MES, IoT, etc. Somewhere, within that blur of rapidly flowing real-time data, is the insight that could change your business.

You schedule a doctor's appointment and immediately your phone buzzes with a notification -- you're now eligible to save a few hundred bucks on your deductible. It may not be a reality quite yet, but experts at UPMC Enterprises say machine learning, advanced access to patient data, and artificial intelligence could soon make your medical care a lot more personal. "Imagine getting an alert that tells you you're close to getting a deduction," said Mohinder Dick, senior software architect at UPMC Enterprises. "I routinely get those kinds of updates from my cable company or Amazon. Why can't we get the same convenience from health care?"

No company is immune to cyber criminal activity. In 2013, Target was hacked despite receiving as many as 10,000 security alerts per day. While Target is a Fortune 100 retailer, even medium-sized companies have to sift through hundreds of thousands of alerts each year. Alerts are investigated before being categorized as false positives and ultimately ignored, but most alerts are idiosyncratic to a product or application with little context of the overall business impact. To prevent financial and reputational loss, security teams are driven to find the most critical needles in an ever-growing haystack of security information.

"Empower bottom-up innovation and amazing things will happen." He was responsible for one of those amazing things: a way to help Spotify users discover new music called Discover Weekly. This tool launched about a year ago; it now has 40 million users and is helping to build the careers of new artists. Newett joined Spotify in 2013, initially working on a team developing a web page with personalized information, news about artists, album releases, and local concerts, along with a recommender system that offered suggestions of albums a user might find appealing. The recommendation feature, Newett recalled, seemed like a good idea, but wasn't heavily used.

The enterprise, as always, is at the forefront of virtually all the multiple technology revolutions taking place today. From Big Data and the Internet of Things to virtual infrastructure and digital business processes, IT is driving the transformation from old-style systems and infrastructure to highly available, highly intelligent applications and services. But sometimes it helps to stop for a moment and see where all this is headed and what work, and life, would be like if all of these developments come to fruition. To my mind, the most consequential advancements are coming in the areas of the IoT and artificial intelligence. How, exactly, will the world function once it has access to a global, interconnected computing environment that touches every device on the planet?

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city – in areas as diverse as transportation, health care and education - and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies. Titled "Artificial Intelligence and Life in 2030," this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines. "We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life," said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. "But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared." The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford.

Jibo is a robot that understands speech, has a moving body that helps him communicate more effectively, and express emotions. Jibo has cameras and microphones to make sense of the world around him, including detecting where sounds come from and recognizing and tracking people. He has a display to show images, an eye that can morph into shapes at will, and a touch interface as a complementary input modality. Jibo encompasses the ultimate human-machine interface, with the potential of becoming a new interaction paradigm. In this talk I will take the audience through a journey in making such a complex devices and the challenged faced by the sheer complexity of integrating a large number of technologies in a character robot device for the home.